Question: Differentiate between overfitting and underfitting in the context of machine learning models.Answer: Overfitting occurs when a model learns the training data too well, capturing noise and producing poor generalization on new data. Underfitting happens when a model is too simple to capture the underlying patterns in the data, resulting in poor performance on both training and test sets. |
Save For Revision
Bookmark this item, mark it difficult, or place it in a revision set.
Log in to save bookmarks, difficult questions, and revision sets.
Is it helpful? Yes No
Most helpful rated by users:
- Explain the purpose of an activation function in a neural network.
- What is transfer learning, and how is it used in deep learning?
- What is a convolutional neural network (CNN), and how is it different from a fully connected neural network?